Agent-Based Modeling emerged as late as the 1990s in the domain of computational social science ([1]}, [2]}) for simulation of artificial societies and their underlying interactions and outcomes. In such models, the behaviors of individuals (called agents) and their mutual interactions are represented mathematically, to observe the outcomes of systems which are difficult to express mathematically. Agent-Based Modeling has also been used in the domains of economics ([3]}), ecology ([4]}) and population biology ([5]}). Agent-Based Modeling has tremendous potential for modelling urban systems, as detailed in [6]} to simulate the interactions of all stakeholders with their urban environment. [7]} and [8]} explore temporal changes in urban sprawl and land-use compare ABMs with Cellular Automata-Based models. In these works, agents represent residents in a city and rule-based models are used to simulate their interactions [9]}, [10]}. Recent work on ABMs focuses on modelling specific unique characteristics/aspects of cities in greater detail. Works such as [11]}, [12]}, [13]}, [14]}, [15]}, [16]} have focused on modeling different aspects of urban life, including urban population growth, pollution and vulnerability to climate change, mobility and traffic management, resource planning and so on. Several ABM-based software packages like MATSIM [17]} and UrbanSim [18]} have also been developed.
